Digital pathology equipment is often used to produce digital images of microscope slides. Pathologists and histotechnologists often visually examine the digital images to obtain information about tissue samples and to identify the most appropriate treatment to improve a clinical outcome. To produce color images, automated slide scanners often acquire images in each of red, green, and blue color channels and combine the images to produce an RGB image.
Scanners can further acquire a plurality of image channels with different spectral characteristics, like fluorescence or brightfield imagers with a bench of multiple or tunable filters to acquire image data. In order to achieve suitable image data, automated slide scanning often includes automatically scanning a tissue sample at a large number of different Z-planes. Many captured images provide little or no value because the image data is often out of focus in most of the Z-planes. This problem affects fluorescence and brightfield imaging using a filter bench, and RGB sensor, or any other method to acquire spectral characteristics.
For RGB-imaging, the Z-plane for the best focus in the blue or green color channel may not be the Z-plane for the best focus in the red color channel, especially if the features being imaged are small (for example, less than the wavelength of light). For multispectral imaging, the Z-plane for the best focus might be different for each individual channel. Image blur in one color channel can impair the overall color image quality leading to serious problems with interpretation, diagnosis, and/or automated image analysis.
To reduce blur, color slide scanners can acquire a complete Z-stack of images (e.g., a set of Z-stack of images for each color channel) and use complex auto-focus algorithms to create a single image from the Z-stacks. However, this requires significant acquisition time, memory to store a large amount of Z-stack data, and significant processing time to analyze the Z-stack data and to generate the color image.
More specifically, the Z-stack is composed of several (typically 3 to 15) images (or layers) for each color channel represented in the tissue being scanned. Acquiring a Z-stack is very time-consuming in that, as an example, the imaging of 7 layers takes nearly 7 times as long as an ordinary scan.
The problem is that the high magnification lenses needed for digitization of pathology slides exhibit an extremely narrow depth of field and therefore their imaging ability is limited by chromatic aberration. This means that if the lens focus is set so as to ensure that the elements of the specimen on the slide that are near to one color are best focused, the objects that are very different from that color will be somewhat blurred. In other terms, for different colors of interest, such as green and red, the z layer for the best focus may be so different that if the focusing algorithm is optimized for green objects, then red objects may be frequently out of focus.
Instead of, or in addition to, blurring from this effect, if an object is surrounded by material of a very different color, the object color may be mixed with that of the surrounding material because of optical diffraction effects. So, as used herein, the “best focus” does not necessarily mean the “sharpest focus”, but instead it may mean the focus at which each object is best distinguished from its surroundings or from other objects from which it is desirable to distinguish it, whether or not they are nearby.
Alternatively, conventional color slide scanners can select a focus (or focal) plane for one channel and then scan other channels at the selected focus plane. For example, a focus plane can be selected for the green channel. The slide scanner acquires images in the red and blue channels at that focus plane to produce a color or multi-spectral image. However, the common focus plane used for acquiring images of all of the channels may not be the best focus plane for each channel, resulting in unwanted image blur in the composite image for features that are dominated by colors other than the one that dominated the focusing procedure.
The following conventional focusing methods have been proposed. One such method is the “best autofocus trajectory from a gray-scale image” method that is implemented in Ventana Medical Systems, Inc. scanners. While this method provides a high scan speed, there remains a continuous need for improvement, particularly with respect to the scanning focus for the color channels that are relatively different in spectrum from the color that dominates the gray-scale image.
According to another exemplary conventional focusing method, the scanner system acquires and stores a Z-stack of images in such a way that the specimen is fully imaged at each value of z. The range of z is chosen so that all of the present chromatic aberration is covered; that is, every color in the tissue will be in good focus in at least one of the layers in the Z-stack. This results in an image of the specimen at high magnification for each layer of the Z-stack for each color channel. Then, an image synthesis algorithm capable of creating a single image from such a Z-stack of images is employed to get a composite image showing all of the color channels in good focus. This approach provides high image quality, while resulting in prohibitive scan times and data file sizes.
Yet another scanning method includes the step of pre-digitization calibration with a calibration sample, in order to establish the value of z for the best focus for each of the various colors of interest in a field of view. The output of this step is often a lookup table or calibration curve that guides the subsequent digitization of slides.
There is therefore a need for new computer-based auto-focus systems, computer program products, and associated methods for digitally imaging microscope slides at a high speed, while avoiding the acquisition and storage of a complete Z-stack of images for each color channel.